Cited by 151Heart Rate Variability and Autonomic ControlSepsis Diagnosis and TreatmentNon-Invasive Vital Sign Monitoring

Clinical review: A review and analysis of heart rate variability and the diagnosis and prognosis of infection

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Ahmad, Saif, Tejuja, Anjali, Newman, Kimberley D, Zarychanski, Ryan, Seely, Andrew JE·2009·Critical Care

Abstract

Bacterial infection leading to organ failure is the most common cause of death in critically ill patients. Early diagnosis and expeditious treatment is a cornerstone of therapy. Evaluating the systemic host response to infection as a complex system provides novel insights: however, bedside application with clinical value remains wanting. Providing an integrative measure of an altered host response, the patterns and character of heart rate fluctuations measured over intervals-in-time may be analysed with a panel of mathematical techniques that quantify overall fluctuation, spectral composition, scale-free variation, and degree of irregularity or complexity. Using these techniques, heart rate variability (HRV) has been documented to be both altered in the presence of systemic infection, and correlated with its severity. In this review and analysis, we evaluate the use of HRV monitoring to provide early diagnosis of infection, document the prognostic implications of altered HRV in infection, identify current limitations, highlight future research challenges, and propose improvement strategies. Given existing evidence and potential for further technological advances, we believe that longitudinal, individualized, and comprehensive HRV monitoring in critically ill patients at risk for or with existing infection offers a means to harness the clinical potential of this bedside application of complex systems science.

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Crossref · 10.1186/cc8132

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  • The finding of association between reduced HRV and poor outcomes is consistent with the theory of 'critical slowing down'.

    “This finding is consistent with the theory of “critical slowing down,” where decreasing variability in biological systems signals impending state transitions20.”

    From Machine learning predicts sepsis deterioration trajectories. (2026) · cites this paper as [20]

    The Prognostication section links reduced HRV measures with deterioration and mortality, and the Discussion links decreased variation with infection severity. But the paper does not identify this pattern as “critical slowing down” or say that decreasing variability signals impending state transitions. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 1

  1. Pramod J Singh A Sepsis biomarkers Am J Med 2008 121 e11 author reply e13 10.1016/j.amjmed.2007.12.009 18501208 · DOI

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Authors
Ahmad, S., Tejuja, A., Newman, K. D., Zarychanski, R., & Seely, A. J.
Affiliations
  • Ottawa Hospital Research Institute (CA)
  • CancerCare Manitoba (CA)
  • University of Ottawa (CA)
Corresponding author
Seely, Andrew JE
Venue
Critical Care
Published
2009
Volume
13
Issue
6
Pages
232
ISSN
1364-8535 (ISSN-L)
OpenAlex
W2112011799
Cited by
151
References
68
Citations by year
2026: 3 · 2025: 6 · 2024: 7 · 2023: 6 · 2022: 12 · 2021: 17 · 2020: 17 · 2019: 11 · 2018: 7 · 2017: 9 · 2016: 11 · 2015: 9 · 2014: 8 · 2013: 11 · 2012: 7
FWCI
0.85
Type
journal article
Language
en
Open access
Locations
  • Critical Care (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • University of Ottawa
  • Ottawa Hospital Research Institute
  • Canadian Institutes of Health Research
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
Keywords
heart rate variability, bacterial infection, sepsis, early infection detection, prognosis, critically ill patients, complex systems science, spectral analysis of HRV, infection severity
MeSH terms
Bacterial Infections, Heart Rate, Humans, Prognosis, Resuscitation, Observer Variation, Critical Illness

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